Cloud computing offers users the ability to access large pools of computational and storage resources on demand, alleviating businesses (e.g., cloud consumers) the burden of managing and maintaining information technology (IT) assets. Cloud providers use virtualization technologies (e.g., VMware®) to satisfy consumer submitted workloads by consolidating workloads and applying resource assignments. The consolidation and assignment settings are often static and rely on fixed rules that do not typically consider the real-time resource usage characteristics of the workloads, let alone the performance impact of colocated workloads. Current systems charge cloud consumers based on the amount of resources used or reserved, with minimal guarantees regarding the quality-of-service (QoS) experienced by the cloud consumers' applications (e.g., workloads) and thereby the experience of the application users. Accordingly, cloud consumers find cloud providers attractive that provide resources (e.g., adequate fraction of hardware infrastructure) to meet the maximum level of QoS guarantee for workloads of cloud consumers.
As virtualization technologies proliferate among cloud providers, consolidating multiple cloud consumers' applications onto multi-core servers improves resource utilization for the cloud providers. Existing tools use random provisioning with static rules that may lead to poor workload performance (e.g., failing to meet QoS guarantee for workloads of cloud consumers) and/or inefficient resource utilization, and perform the application profiling and resource adjustment manually. In addition, the consolidation of multiple cloud consumers' applications (e.g., workloads) introduces performance interference between colocated workloads, which significantly impacts the QoS of each consolidated users' applications workloads.